Last week, I read an interesting article about Gartner’s 10 predictions for the future. Generally, Gartner believes that our lives will become increasingly dominated by digitalization and in the enterprise, digital transformation will accelerate. One of Gartner’s predictions in particular caught my attention: the automation of enterprise content generation. In Gartner’s estimation, automated content will be around 20% for all business content by the year 2018. This in and of itself seems like a conservative prediction. However, Gartner goes further arguing that not only will 20% of the automated content be computer written, but it will be totally indistinguishable from content written by humans. In a manner of speaking, Gartner believes that computers will pass the Turing Test in the near future.

Gartner is world renowned for its accurate predictions of business, as well as its conservative and measured approach to those predictions. So where do these predictions come from?

The Beginnings of Content Automation

Today, language generation software has entered the next generation, with solutions capable of producing text that is indistinguishable from that written by a human. However, the quality of the text was not the main hurdle. Initially, Natural Language Generation (NLG) software could not be installed on a company’s server. Only a highly technical team of Artificial Intelligence PhDs could make the software work. In short, first generation NLG was not scalable. However, something changed in the last several years with the advent of next generation NLG.

What’s Next for Natural Language Generation?

Next generation NLG can not only be installed on a company’s server securely behind their firewall, but it can be configured by employees within that company. More importantly, any business user can configure the software. The days of needing AI PhDs to build applications are over. Essentially, today for the first time content automation software is easy to adopt, configure, and deploy. Or, to put it another way, NLG software now is easily scalable.

According to Gartner, 20% of content generated by machines will include documents like market analysis, legal documents, new stories, and more.

Gartner’s predictions don’t seem so futuristic. Yseop’s self-service software is already generating content for the global Fortune 500 on both sides of the Atlantic and the content generated by Yseop Compose is indistinguishable from the content generated by those companies’ employees. Companies can configure Yseop Compose themselves, telling it what rules to follow. Once programmed, Yseop Compose applies company best practices to scale, turning data into written content with the click of a button.

It’s not an accident that leading global companies are adopting NLG. Today, in the age of Big Data, the conventional data to insight process is too slow and too costly. This conventional process relies on data aggregators and analysis followed by complex dashboards. However, the problem is that a dashboard can’t tell you why. The process to draw insight from a dashboard still requires an expert to interpret the information. With Yseop Compose, drawing insight from data is as simple as clicking a few buttons and reading a written report. If I were to make a prediction of my own, I truly believe more than 20% of business content will be written automatically in 2018.

Tiphaine Coupel

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Yseop is a global enterprise software company with offices in New York, London, Paris, Dallas, and Lyon. Its enterprise customers are mainly in the global Fortune 1000, and on a daily basis, 50,000 end users employ Yseop. Yseop has led the international technology scene and has quickly been recognised by artificial intelligence and business intelligence leaders thanks to its innovative solutions that translate data analysis into written insight.

Yseop has a unique, patented system, which is the only self-service software on the market that can reason and clearly express conclusions in multiple languages, in real-time. Yseop’s software turns data into narrative in English, French, German, and Spanish, all at the speed of thousands of pages per second.